首页> 外文会议>Document Analysis Systems, DAS, 2008 Eighth IAPR Workshop on >Word and Symbol Spotting Using Spatial Organization of Local Descriptors
【24h】

Word and Symbol Spotting Using Spatial Organization of Local Descriptors

机译:使用局部描述符的空间组织识别单词和符号

获取原文

摘要

In this paper we present a method to spot both text and graphical symbols in a collection of images of wiring diagrams. Word spotting and symbol spotting methods tend to use the most discriminative features to describe the objects to be located. This fact makes that one can not tackle with textual and symbolic information at the same time. We propose a spotting architecture able to index both words and symbols, inspired in off-the-shelf object recognition architectures. Keypoints are extracted from a document image and a local descriptor is computed at each of these points of interest. The spatial organization of these descriptors validate the hypothesis to find an object (text or symbol) in a certain location and under a certain pose.
机译:在本文中,我们提出了一种在接线图图像集中发现文本和图形符号的方法。单词发现和符号发现方法倾向于使用最具区分性的功能来描述要定位的对象。这一事实使人们无法同时处理文本和符号信息。我们提出了一种发现架构,该架构能够在现成的对象识别架构的启发下,同时对单词和符号进行索引。从文档图像中提取关键点,并在每个这些关注点上计算局部描述符。这些描述符的空间组织验证了这一假设,以便在特定位置和特定姿势下找到对象(文本或符号)。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号